Join our customer's team as a Remote Household Task Video Recorder and make an impact on the future of robotics and machine learning. You will contribute high-quality synchronized motion and video data that powers advanced activity recognition systems—right from your home. This is a unique chance to blend technology and daily activity in a role tailored for detail-oriented, tech-savvy professionals.
Key Responsibilities:
- Capture synchronized motion data with your smartphone’s IMU sensors while performing specified household tasks.
- Record high-fidelity video footage alongside sensor data to enhance dataset accuracy and reliability.
- Follow strict technical protocols to ensure submission quality, precise labeling, and data determinism.
- Deliver a consistent minimum of 10 hours of approved video data each week, meeting project requirements.
- Engage proactively with the team to clarify assignment guidelines and share actionable feedback on data processes.
- Meet deadlines by organizing, preparing, and submitting data in line with project milestones and quality standards.
- Complete required device compatibility checks and participate in a custom AI-enabled interview process.
Required Skills and Qualifications:
- Track record of following rigorous protocols and technical procedures in a professional setting.
- Exceptional written and verbal communication skills, with the ability to document work clearly and collaborate remotely.
- Strong proficiency in using smartphones and mobile apps for data collection tasks.
- Physical ability to safely and accurately perform repetitive household movement tasks.
- Demonstrated commitment to delivering reliable, consistent output in a time-sensitive environment.
- Access to a compatible smartphone for high-quality IMU and video data capture.
- Eligibility to work from one of these U.S. states: Alabama, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Mississippi, New Hampshire, North Carolina, North Dakota, Oklahoma, Pennsylvania, South Carolina, Tennessee, Texas, Utah, or Wisconsin.
Preferred Qualifications:
- Background in robotics, kinesiology, human motion analysis, or sensor-based data collection projects.
- Experience structuring and labeling large datasets for machine learning applications.
- Familiarity with activity recognition or activity segmentation protocols.
